Product teams today rely deeply on real-time insights from user interactions. Low-latency event collection is foundational for product analytics, growth experiments, and customer experience optimization. Many organizations require data to stream in real-time into analytical backends like ClickHouse or BigQuery, but prefer not to rely on third-party vendors due to compliance, cost, and control considerations.
TLDR
If you’re looking to stream product events to ClickHouse or BigQuery with minimal delay and no third-party vendors, these are the six tools engineering teams trust the most. They offer low-latency, open-source or self-hostable options, supporting customization and scaling. Tools like Redpanda, Vector, and Benthos provide resilient pipelines, while OpenTelemetry and Kafka give you control over trace data and message distribution. Explore what best fits your stack and security requirements.
Why Low-Latency Event Collection Matters
Modern product teams demand real-time feedback loops. Whether you’re A/B testing features, tracking user flows, or understanding product performance, stale or delayed event data can lead to inaccurate insights. Streaming events directly into warehouses like ClickHouse or BigQuery reduces dependencies and latency, enabling faster decisions and improving observability.
Relying solely on third-party analytics solutions can introduce:
- Latency overheads from routing and processing delays
- Data privacy concerns when sharing behavioral data externally
- Higher costs related to licensing and per-event pricing
This is where self-managed event collectors become indispensable.
Top 6 Low-Latency Event Collectors
1. Redpanda – A Kafka-Compatible Streaming Platform Without JVM
Redpanda is a high-performance, Kafka-compatible streaming engine designed for low-latency and resource efficiency. Unlike Apache Kafka, it is implemented in C++ and runs on a single binary without the Java Virtual Machine (JVM), reducing memory usage and startup time.
Features that make Redpanda ideal for real-time product event streaming include:
- Kafka API Compatibility — Integrate instantly with your Kafka producers and consumers
- Single Binary Operation — Reduces operational complexity
- Low Latency — Targeted at less than 1ms end-to-end latency
You can connect Redpanda with tools like ClickHouse Sink Connector or ingest events using a custom consumer that writes to BigQuery’s streaming API.
2. Vector – Fast, Extensible Open Source Observability Pipeline
Vector by Datadog is another standout choice for product event ingestion. It’s a lightweight, open-source tool designed to collect, transform, and route logs, metrics, and events with ultra-low overhead. It supports WASM-based logic, making it a powerful tool for customizing event transformation at the edge of your infrastructure.
Key capabilities:
- Sinks for ClickHouse and BigQuery — Send events directly without needing intermediate queues
- Schema enforcement — Crucial for maintaining data quality in warehouses
- Edge-to-core tracing — Embed tracing data along with event metrics easily
Teams often deploy Vector as a daemonset on Kubernetes, collecting frontend and backend telemetry and routing it directly to ClickHouse in real-time.
3. Kafka with Fluent Bit – The Customizable Power Duo
If you’re running Apache Kafka already, pairing it with Fluent Bit offers a performant event pipeline. Fluent Bit is an open-source log processor and forwarder optimized for lightweight environments. It can parse structured product events from microservices or frontend ingestion and forward to Kafka topics.
From Kafka, you have two powerful routing options:
- Use Kafka Connect with sink connectors for ClickHouse or Google BigQuery
- Consume with a custom service that applies transformations before loading into your warehouse
This combo lets teams handle high-volume streaming workloads without introducing third-party vendors. While not the easiest to configure, it’s extremely versatile for sophisticated ETL pipelines.
4. Benthos – Streamline Data Without Writing Code
Benthos is a lesser-known but powerful single-binary streaming tool, purpose-built for resiliency in moving data. It provides YAML-based configuration and doesn’t require writing custom code to parse, modify, and route product events.
Benefits of using Benthos include:
- 100+ Input and Output Plugins — Including Kafka, HTTP, File, and direct database sinks
- Flexible Pipelines — Use branching, filters, data enrichment, and batching
- Strong Observability — Native support for metrics and tracing with Prometheus
Benthos is ideal for dev teams who want a flexible pipeline without maintaining infrastructure like Kafka, and it connects seamlessly to ClickHouse or BigQuery directly via HTTP writers or custom plugins.
5. OpenTelemetry Collector – Unified Ingest for Events, Logs, and Traces
While OpenTelemetry (OTel) is primarily known for tracing and metrics, the OTel Collector has evolved into a robust tool for event ingestion—especially when teams want consistency across observability and product analytics pipelines.
Why engineering teams use it:
- Wide support for protocols and exporters including HTTP, gRPC, and OTLP
- Standardization of telemetry data before routing to analytics backends
- Strong integration with cloud-native stacks like Kubernetes, Prometheus, and Jaeger
You can set up exporters to stream structured event telemetry from the OTel Collector directly to BigQuery via Pub/Sub or to ClickHouse through custom adapters.
6. Snowplow Open Source – Event Analytics with Full User Data Ownership
Originally known for behavioral analytics, Snowplow’s open-source solution now doubles as a powerful, real-time event pipeline. It supports custom event schemas, making it perfect for teams who want full transparency and control over their product event collection stack.
Features include:
- Real-time streaming with Kafka and GCP Pub/Sub
- Build-your-own pipeline architecture from trackers to loaders
- Strong schema validation with support for JSON schemas
Snowplow can stream events to BigQuery with minimal delay and integrates with ClickHouse using community-developed loaders. Ideal for mature product teams willing to invest in a highly customizable analytics stack.
Final Thoughts
Choosing the right event collector stack depends on your team’s infrastructure, language preferences, latency needs, and compliance requirements. Tools like Redpanda and Benthos offer simplicity and speed, while solutions like Kafka + Fluent Bit and OpenTelemetry provide massive flexibility and ecosystem support.
Importantly, all six tools highlighted avoid third-party vendor lock-in, giving your team greater control over data privacy and operational costs. For any modern dev team wanting end-to-end real-time visibility into product usage, mastering one or two of these tools is game-changing.
Recommended Next Steps
- Start a PoC with one of these collectors routed into your ClickHouse or BigQuery instance
- Measure end-to-end latency and processing reliability under load
- Evaluate observability features (metrics, logs, retry behavior)
- Assess transformation and schema validation capabilities
Low-latency product analytics is no longer exclusive to big tech – with the right tools, any team can build robust, self-managed streaming pipelines.
